74 research outputs found

    TGA: Team game algorithm

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    Lately, there is a growing interest in conducting research on optimization algorithms due to their wide range of engineering applications. One of the optimization algorithms' categories is evolutionary algorithms which are inspired from the natural behavior of animals and humans. Further, each of the evolutionary algorithms has its own advantages and disadvantages in convergence accuracy and computational time. In the present paper, a novel solution search algorithm taken from the team games is introduced. This evolutionary algorithm named Team Game Algorithm (TGA) involves passing a ball, making mistakes and substitution operators. Comparing the TGA's results to the outcomes of other well-known algorithms for unimodal and multimodal test functions elucidates the successful design of the proposed heuristic algorithm. Keywords: Optimization heuristic algorithm, Team game algorithm, Passing operator, Mistake operator, Substitution operator, Unimodal and multimodal test function

    A new mechanical design for legged robots to reduce energy consumption

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    Many legged robots have been designed and built by universities, research institutes and industry; however, few investigations regard energy consumption as a crucial design criterion. This paper presents a novel configuration for legged robots to reduce the energy consumption. The proposed leg can be either used as a single leg or easily attached to bodies with four, six and eight legs. This mechanism is a parallel four-bar linkage equipped with one active and four passive joints. In fact, the usage of the passive elements leads to simple feed-forward control paradigms. Moreover, another distinctive feature of this design is the arrangement of one-way clutches and flat springs to store the potential energy for utilizing it in the next step. A locomotion prototype of the proposed mechanical structure is built and its simulation is also presented in this paper. Comparing the results with other structures demonstrates the superiority and efficiency of this work regarding energy consumption problem.</p

    The efficacy of psycho training on improvement of organizational behavior and mental health

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    Introduction: One of the most important issues of organizations in the modern age is to maximize their efficiency via improvement of organizational behavior. Organizational behavior is directly linked to mental health and recent studies have shown the major role of religion in maintaining mental health of people. The aim of the study was to investigate the efficacy of psycho-religious training on improvement of the organizational behavior and mental health.Method: A group of 120 white collar personnel (60 females and 60 males) chosen by cluster sampling &amp; divided randomly into two equal experimental and control groups (n=60; 30 female &amp; 30 male). The experimental trial was the administration of the psycho-religious training for three weeks, which consisted of twelve 120-minute discussion-group sessions during 12 weeks. In order to assess the mental health, GHQ-28 was administered as pre-test and post-test in both groups.Findings: The results of the independent and dependent t-test indicate the positive effect of psycho-religious training on the mental health of the participants in the experimental group in indices of anxiety/insomnia, severe depression, and total health (p&lt;.05). There were no significant gender differences.Discussion and conclusion: These findings suggest that incorporation of religious training within the usual modalities of psychological interventions would be beneficial and increase the levels of mental health and organizational behavior. Implications and suggestions are discussed.Keywords: Psycho-religious education, psychoeducation, religion, organizational behavior, mental health, white collar, labor forc

    Sediment yield estimation using a semi-quantitative model and GIS-remote sensing data

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    Aggregate breakdown and surface seal development influenced by rain intensity, slope gradient and soil particle size

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    Aggregate breakdown is an important process which controls infiltration rate (IR) and the availability of fine materials necessary for structural sealing under rainfall. The purpose of this study was to investigate the effects of different slope gradients, rain intensities and particle size distributions on aggregate breakdown and IR to describe the formation of surface seal. To address this issue, 60 experiments were carried out in a 35 × 30 × 10 cm detachment tray using a rainfall simulator. By sieving a sandy loam soil, two sub-samples with different maximum aggregate sizes of 2 mm (<i>D</i><sub>max</sub>2 mm) and 4.75 mm (<i>D</i><sub>max</sub>4.75 mm) were prepared. The soils were exposed to two different rain intensities (57 and 80 mm h<sup>&minus;1</sup>) on several slopes (0.5, 2.5, 5, 10 and 20%) each at three replicates. The result showed that for all slope gradients and rain intensities, the most fraction percentages in soils <i>D</i><sub>max</sub>2 and <i>D</i><sub>max</sub>4.75 mm were in the finest size classes of 0.02 and 0.043 mm, respectively. The soil containing finer aggregates exhibited higher transportability of pre-detached material than the soil containing larger aggregates. Also, IR increased with increasing slope gradient, rain intensity and aggregate size under unsteady state conditions because of less development of surface seal. However, under steady state conditions, no significant relationship was found between slope and IR. The findings of this study revealed the importance of rain intensity, slope steepness and soil aggregate size on aggregate breakdown and seal formation, which can control infiltration rate and the consequent runoff and erosion rates

    Sequestration of organic carbon influenced by the application of straw residue and farmyard manure in two different soils

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    Soil organic carbon is one of the most important soil components, which acts as a sink for atmospheric CO2. This study focuses on the effect of different methods of organic matter application on the soil organic carbon sequestration in a 4-month experiment under controlled greenhouse conditions. Three rates of straw residue and farmyard manure were added to uncultivated and cropland soils. Two treatments of straw residue and farmyard manure incorporation were used into: a soil surface layer and 0-20 cm soil depth. The result showed that the application of organic matter, especially the farmyard manure incorporation led to a significant increase in the final soil organic carbon content. Higher amounts of soil organic carbon were stored in the cropland soil than in the uncultivated soil. On average, the soil surface layer treatment caused a higher sequestration of soil organic carbon compared to the whole soil depth treatment. If higher rates of organic matter were added to the soils, lower carbon sequestration was observed and vice versa. The result indicated that the carbon sequestration ranged farmyardmanure > strawresidue and cropland soil > uncultivated soil. The findings of this research revealed the necessity of paying more attention to the role of organic residue management in carbon sequestration and prevention of increasing global warming

    Trajectory Tracking of a Flexible Robot Manipulator by a New Optimized Fuzzy Adaptive Sliding Mode-Based Feedback Linearization Controller

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    This work presents a novel fuzzy adaptive sliding mode-based feedback linearization controller for trajectory tracking of a flexible robot manipulator. To reach this goal, after deriving the dynamical equations of the robot, the feedback linearization approach is utilized to change the nonlinear dynamics to a linear one and find the control law. Then, the sliding mode control strategy is implemented to design a stabilizer for trajectory tracking of the flexible robot. In order to adaptively tune the parameters of the designed controller, the gradient descent approach and the chain derivative rule are employed. Moreover, the Takagi–Sugeno–Kang fuzzy system is applied to regulate the controller gains. Finally, a multiobjective particle swarm optimization algorithm is used to find the optimum fuzzy rules. The conflicting objective functions considered as the integrals of the absolute values of the state error and the control effort should be minimized, simultaneously. The simulation results illustrate the effectiveness and capability of the introduced scenario in comparison with other methods
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